Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/3999
Title: 3D reconstruction of urban areas
Authors: Poullis, Charalambos 
Major Field of Science: Humanities
Field Category: Arts
Keywords: Image reconstruction;Optical radar;Imaging, Three-Dimensional
Issue Date: 2011
Source: International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission, 2011, Hangzhou
Abstract: Abstract Virtual representations of real world areas are increasingly being employed in a variety of different applications such as urban planning, personnel training, simulations, etc. Despite the increasing demand for such realistic 3D representations, it still remains a very hard and often manual process. In this paper, we address the problem of creating photorealistic 3D scene models for large-scale areas and present a complete system. The proposed system comprises of two main components: (1) A reconstruction pipeline which employs a fully automatic technique for extracting and producing high-fidelity geometric models directly from Light Detection and Ranging (LiDAR) data and (2) A flexible texture blending technique for generating high-quality photorealistic textures by fusing information from multiple optical sensor resources. The result is a photorealistic 3D representation of large-scale areas(city-size) of the real-world. We have tested the proposed system extensively with many city-size datasets which confirms the validity and robustness of the approach. The reported results verify that the system is a consistent work flow that allows non-expert and non-artists to rapidly fuse aerial LiDAR and imagery to construct photorealistic 3D scene models.
URI: https://hdl.handle.net/20.500.14279/3999
DOI: 10.1109/3DIMPVT.2011.14
Rights: © IEEE.
Type: Conference Papers
Affiliation : Cyprus University of Technology 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

CORE Recommender
Show full item record

SCOPUSTM   
Citations 50

20
checked on Nov 8, 2023

Page view(s) 50

649
Last Week
0
Last month
7
checked on Nov 21, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.